The statistics in question are five-year survival data. The commentary does a terrific job of explaining why this data — which Komen cites frequently — is meaningless in regard to mammography.

“If there were an Oscar for misleading statistics, using survival statistics to judge the benefit of screening would win a lifetime achievement award hands down,” write the commentary’s authors, Dr. Steven Woloshin and Dr. Lisa Schwartz of the Center for Medicine and the Media at the Dartmouth Institute for Health Policy and Clinical Practice.

Understanding ‘lead time’

Komen featured such statistics, point out Woloshin and Schwartz, in an ad launched last October during "Breast Cancer Awareness Month," which urged women to get screened “now” because “early detection saves lives.” The ad underscored that message by declaring that the five-year survival rate for breast cancer is 98 percent when the disease is “caught early,” but only 23 percent “[w]hen it’s not.”

“This benefit of mammography looks so big that it is hard to imagine why any woman would forgo screening,” write Woloshin and Schwartz. “She’d have to be crazy.”

But it’s the advertisement that’s crazy, not the women responding to it, they say. Here’s why (warning: British spellings):

[S]creening changes the point during the course of cancer when a diagnosis is made. Without mammography screening, a diagnosis is made when the tumour can be felt. With screening, diagnosis is made years earlier when tumours are too small to feel. Five year survival is all about what happens from the time of diagnosis: it is the proportion of women who are alive five years after diagnosis. Because screening finds cancers earlier, comparing survival between screened and unscreened women is hopelessly biased.

The time between when a cancer can be diagnosed by screening and when it can be felt is called the “lead time.” Although a screening test must create lead time to have the possibility of working, lead time can bias survival statistics. Barnett Kramer, director of the National Cancer Institutes’ Division of Cancer Prevention, explained lead time bias by using an analogy to The Rocky and Bullwinkle Show, an old television cartoon popular in the US in the 1960s. In a recurring segment, Snidely Whiplash, a spoof on villains of the silent movie era, ties Nell Fenwick to the railroad tracks to extort money from her family. She will die when the train arrives. Kramer says, “Lead time bias is like giving Nell binoculars. She will see the train — be ‘diagnosed’ — when it is much further away. She’ll live longer from diagnosis, but the train still hits her at exactly the same moment.”

To see how much lead time can distort five year survival data, imagine a group of 100 women who received diagnoses of breast cancer because they felt a breast lump at age 67, all of whom die at age 70. Five year survival for this group is 0%. Now imagine the women were screened, given their diagnosis three years earlier, at age 64, but still die at age 70. Five year survival is now 100%, even though no one lived a second longer.

Another factor

Lead-time distortion is not the only reason five-year survival data is meaningless in the context of screening.

“[S]creening detects some cancers that would never have killed — or even caused symptoms during a person’s lifetime,” explain Woloshin and Schwartz. “That is because some cancers detected by screening grow extremely slowly or not at all. Overdiagnosis distorts survival statistics because the numerator and denominator now include people who have a diagnosis of cancer but who, by definition, survive the cancer. Overdiagnosis inflates survival statistics even when screening fails to save lives. The more overdiagnosis that occurs, the greater the inflation.”

Even doctors are fooled by five-year survival statistics. A recent national survey conducted by Woloshin and Schwartz made the troubling finding that most primary-care physicians in the U.S. mistakenly believe improved survival rates are evidence that screening saves lives.

More reliable numbers

“The only reliable way to know that a screening test works is the extent to which it reduces deaths in a randomized trial,” write Woloshin and Schwartz.

And what do those trials tell us? They show that mammography screening reduces the likelihood that a woman in her 50s will die from breast cancer over the next 10 years from 0.53 percent to 0.46 percent, a difference of 0.07 percentage points.

That’s a long, long way from the 75 percentage points cited in the Koman ad. Furthermore, as Woloshin and Schwartz point out, the ad says nothing about the harms of screening: the unnecessary biopsies that occur with false positive results and the unnecessary chemotherapy, radiation or surgery that women go through when they are overdiagnosed.

“Women need much more than marketing slogans about screening: they need — and deserve — the facts,” write Woloshin and Schwartz. “The Komen advertisement campaign failed to provide the facts. Worse, it undermined decision making by misusing statistics to generate false hope about the benefit of mammography screening. That kind of behaviour is not very charitable.”

The commentary is part of BMJ's "Not So" series, which the editors call an “occasional series highlighting the exaggerations, distortions, and selective reporting that make some news stories, advertising, and medical journal articles ‘not so.’” I wish I could send MinnPost readers to the BMJ website to read it, but for reasons that are inexplicable to me, the journal has decided to keep this paper behind a paywall.

Comments (10)

I'm always frustrated by the repeated claims that preventative medicine will cure the problems of our medical system by controlling costs and saving lives. This article if a perfect illustration of the fallacy of that claim. Medicine, preventative or otherwise, is still medicine, it's treatments and procedures that cost money. Of course providers get excited about expanded PM because it means billions of dollars worth of additional treatments, tests, and procedures. Remember, it means billions of dollars worth of additional treatments, tests, and procedures. Sometimes these tests and procedures save lives, sometimes they prolong lives, and sometimes they make no difference. Preventative medicine rarely prevents illness, it simply detects it earlier, and that doesn't always save money. Preventative medicine is clearly an essential part of any good health care system, but we have to stop selling it as some kind of panacea of salvation and cost control.

Are two different things.
This article is about the benefits of detecting a given pathology (breast cancer) early. As with prostate cancer, the data regarding mortality, the ultimate criterion for program effectiveness are weak at best.
Prevention, on the other hand, occurs BEFORE the illness. Reducing the number of people who smoke prevents (or at least decreases the likelihood) the occurrence of lung cancer. This is what preventive medicine is about.
Komen is primarily about the detection of an existing illness, not preventive medicine.

are listed on its Web site:http://ww5.komen.org/CorporatePartners.aspx
GE is listed; Siemens is not.
You can go through all sixty or so on the site.
You'd have to dig through Federal documents on file to find the actual amounts.

However, what I'd like to know is whether an earlier diagnosis leads to a longer average life span or greater chance of remission. If so, how much.

It appears that there is SOME data on that. In this article, screening may increase the lifespan of 7 of every 1000 women. So, there is some net benefit to screening. The question is the significance of this number. That lifespan is added during the ages of their 50's and 60's--still relatively young. These 7 women will live to an age closer to their 70's, and their families will have their mothers, sisters, aunts, and grandmothers longer, too. That is, if we go by the numbers I can find (from the year 2000), about 11,200 women would live into their 70's rather than dying in their 60's. Is there a net benefit to that? For those particular women and their families, almost certainly. If enough women are convinced that they should get a mammogram because of the Komen ads, then they would likely see those statistics as being important.

Certainly, though, there's no room for such large fibs on the Komen foundation's part. There is a LOT of money that goes through their hands. The effect of their ads is not only breast cancer awareness, but gobs of money funneled through their foundation--used to pay various companies, advisers, coordinators, etc. Money that could have gone to more specific research for preventing breast cancer or treating breast cancer more effectively.

"And what do those trials tell us? They show that mammography screening reduces the likelihood that a woman in her 50s will die from breast cancer over the next 10 years from 0.53 percent to 0.46 percent, a difference of 0.07 percentage points."

In other words, the further out you go, the less associated mammograms may be with long term survival rates.

Paul, anti-smoking campaigns are public health, not medicine. Preventative medicine is procedures and tests, not merely advice. Public health tells people to lose weight and avoid type II diabetes, that's advice, not medicine. Preventative medicine does blood tests to see if people are developing type II diabetes, and then treats it with medication, eye exams, and blood glucose monitoring.

Both advice and PM cost money, and the more you dispense them, the more it will cost. PM doesn't "prevent" diabetes, it detects it and treats it. Now that treatment may prevent complications such as eye and nerve damage, but your substituting one form of treatment for another, not eliminating treatment, so you can't assume you're going to save money. Decades of PM while a good idea, better to not go blind than go blind, are not necessarily less expensive. Another example is heart disease. A couple recent studies have shown that while tests and screening for high blood pressure and cholesterol, EKG's etc. followed up with drug treatment are preventing heart attacks, decades of such treatment are no cheaper than heart attacks followed by a week of hospitalization. And of course some preventative treatments such as bypass surgery are very expensive. And for all of this heart disease remains the number one killer in the US.

Again, I'm not saying preventative medicine is a bad idea, it's not. PM is an essential part of any good health care system. But we have to stop selling it as cost control of any kind. More than likely the more PM we make available, the higher health care costs will be. Now that doesn't mean we can't control or reduce costs elsewhere, but PM is far too frequently sold as a cost control mechanism.

We're usually pretty in sync, but you missed the rest of my post (and the statistics you refer to do not necessarily mean what you're saying).

That being said, you are right in that preventative medicine isn't always exactly described correctly. The use of prenatal vitamins is an example of preventative medicine that not only works, but saves money. The use of immunizations is another example. A mammogram is not preventative medicine. It is a way to catch a disease earlier, and hopefully increase the options for treating and/or curing it while it's the most treatable or curable. In other words, it is disease screening with a slight benefit toward survival.

My point was--how do we get an accurate reflection of the benefit of such screening? Clearly, there is a benefit for some women to detect the disease earlier. I would imagine we'd see benefits for other disease screening procedures. But a mammogram is not cheap, and when you get one on the order of every 5 years to every year, depending on age, risk, history, etc., that adds up. So, what is the overall benefit? Well, that depends on how much you value those 7 women out of every thousand. Do they have a monetary value?

Also, screening procedures provide data points for retroactive studies. Data mining has become an important non-invasive tool for studying the effectiveness of various treatments available for a disease. Comparing data from screening procedures to outcomes may help narrow down the correct treatment for the correct group of people. (Diseases, particularly cancer, are frustratingly individual.)

Nope. It's not cheap. Until we can agree on the monetary value of a human life, there's no way to identify what the right cost is, either.

I don't think we need to put a monetary value on human life, I think we just need to decide to provide and pay for best practices in health care and make them universally available. We're the only post industrial democracy in the that hasn't made that decision yet.